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dc.contributor.authorCatala, Paul
dc.contributor.authorDuval, Vincent
HAL ID: 7243
ORCID: 0000-0002-7709-256X
dc.contributor.authorPeyré, Gabriel
HAL ID: 1211
dc.date.accessioned2018-03-09T15:28:22Z
dc.date.available2018-03-09T15:28:22Z
dc.date.issued2017
dc.identifier.issn1742-6588
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17539
dc.language.isoenen
dc.subjectSparse Deconvolution
dc.subjectRadon measures
dc.subject.ddc621.3en
dc.titleA Low-Rank Approach to Off-The-Grid Sparse Deconvolution
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe propose a new solver for the sparse spikes deconvolution problem over the space of Radon measures. A common approach to off-the-grid deconvolution considers semidefinite (SDP) relaxations of the total variation (the total mass of the absolute value of the measure) minimization problem. The direct resolution of this SDP is however intractable for large scale settings, since the problem size grows as f2dc where fc is the cutoff frequency of the filter and d the ambient dimension. Our first contribution introduces a penalized formulation of this semidefinite lifting, which has low-rank solutions. Our second contribution is a conditional gradient optimization scheme with non-convex updates. This algorithm leverages both the low-rank and the convolutive structure of the problem, resulting in an O(fdclogfc) complexity per iteration. Numerical simulations are promising and show that the algorithm converges in exactly r steps, r being the number of Diracs composing the solution.
dc.relation.isversionofjnlnameJournal of Physics. Conference Series
dc.relation.isversionofjnlvol904
dc.relation.isversionofjnlissueconférence 1
dc.relation.isversionofjnldate2017
dc.relation.isversionofdoi10.1088/1742-6596/904/1/012015
dc.relation.isversionofjnlpublisherIOP Science
dc.subject.ddclabelTraitement du signalen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2018-04-13T09:17:54Z


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